Having wrapped up a recent flurry of R ANOVA articles (and exhausted my knowledge of the subject), I decided to take a look at the R Tutorial Series' Google Analytics data from the past few months.
Since I posted the Two-Way Omnibus ANOVA article on January 17, we have had about 150 visits per day and over 19,000 total page views. The original introduction to R posts are still the most popular ones here, although a few from the regression and ANOVA series are also represented in the most viewed.
I also wanted to share a funny observation about the patterns of visits to the R Tutorial Series. The following graph portrays our daily viewership over the past few months.

The valleys on the chart correspond to the weekends (evidently when no one wants to read about statistical computing). The initial peaks are Mondays, which happen to be when I most often make new posts. Typically, a slightly higher peak comes on Tuesday, followed by a gradual decline back into the weekend valley. Thus, our visits to the R Tutorial Series end up creating a nice little wave pattern throughout the year. The good news with these numbers is that people are reading the R Tutorial Series and (hopefully) learning to use R and apply it to their daily work, which is the blog's ultimate purpose. I also appreciate all of the comments, questions, and tips that have been posted by readers. Your feedback really helps to improve the tutorials.

Upcoming Plans

As mentioned, I have concluded my planned coverage of ANOVA in R. Thus, we have reached a sort of break period, much like the one that followed last year's spurt of regression tutorials. I do plan to keep writing R tutorials, but for the time being, they may arrive in less predictable intervals and cover a wider variety of content. As always, I welcome contact regarding guest posts, especially on statistical and R content that I have not covered or am not yet familiar with.

2 comments:

Just wanted to say thanks for all the clear and useful instruction that your blog supplies. I work for the department of bioinformatics at the Van Andel Research Institute and your posts have helped me analyze data that is crucial to cancer research and treatment development. Beyond helping people understand how to program in R, you are also making a difference in people's lives who have cancer. Thanks again, and keep up the great work.